Abstract:
In numerous applications, such as tracking physical activity, decoding sign language, and controlling full-body gestures, human position estimation from the video is cruc...Show MoreMetadata
Abstract:
In numerous applications, such as tracking physical activity, decoding sign language, and controlling full-body gestures, human position estimation from the video is crucial. Human pose classification is challenging yet well-researched area. The particular way that human joints are arranged is referred to as pose. The localization of human joints or predetermined markers in images and videos can therefore be defined as the topic of “Human Pose Estimation.” Pose estimate is required for applications like human activity detection, sports, yoga positions, sign language applications, motion. The Mediapipe API is utilized in this study for human classification. This model categorizes human poses while identifying and tracking the actions of individual body parts. This paper demonstrates the adaptability of deep learning techniques and highlights the efficiency and accuracy of the BlazePose API in providing reliable pose landmarks.
Published in: 2023 7th International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS)
Date of Conference: 02-04 November 2023
Date Added to IEEE Xplore: 07 December 2023
ISBN Information: